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Data science ethical considerations: a systematic literature review and proposed project framework

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Abstract

Data science, and the related field of big data, is an emerging discipline involving the analysis of data to solve problems and develop insights. This rapidly growing domain promises many benefits to both consumers and businesses. However, the use of big data analytics can also introduce many ethical concerns, stemming from, for example, the possible loss of privacy or the harming of a sub-category of the population via a classification algorithm. To help address these potential ethical challenges, this paper maps and describes the main ethical themes that were identified via systematic literature review. It then identifies a possible structure to integrate these themes within a data science project, thus helping to provide some structure in the on-going debate with respect to the possible ethical situations that can arise when using data science analytics.

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  1. Syracuse University, Syracuse, USA

    Jeffrey S. Saltz & Neil Dewar

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  1. Jeffrey S. Saltz
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  2. Neil Dewar
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Correspondence to Jeffrey S. Saltz.

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Saltz, J.S., Dewar, N. Data science ethical considerations: a systematic literature review and proposed project framework. Ethics Inf Technol 21, 197–208 (2019). https://doi.org/10.1007/s10676-019-09502-5

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